Applications of the Internet of Things (IoT) in Smart Logistics: A Comprehensive Survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Logistics is a driver of countries' and firms' competitiveness and plays a vital role in economic growth. However, the current logistics industry still faces high costs and low efficiency. The development of smart logistics brings opportunities to solve these problems. As one of the important technologies of the modern information and communication technology (ICT), the Internet of Things (IoT) can create oceans of data and explore the complex relationships between the transactions represented by these data with the help of various mathematical analysis technologies. These features are helpful to promote the development of smart logistics. In this article, we provide a comprehensive survey on the literature involving IoT technologies applied to smart logistics. First, the related work and background knowledge of smart logistics are introduced. Then, we highlight the enabling technologies for IoT in smart logistics. Furthermore, we review how IoT technologies are applied in the realm of smart logistics from the perspectives of logistics transportation, warehousing, loading/unloading, carrying, distribution processing, distribution, and information processing. Finally, some challenges and future directions are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it